In recent years, enterprises have shifted much of their computing needs from enterprise owned and operated computer systems to cloud-computing providers. Cloud-computing providers charge enterprises for use of information technology (“IT”) services over a network, such as storing and running an enterprise's applications on the hardware infrastructure, and allow enterprises to purchase and scale use of IT services in much the same way utility customers purchase a service from a public utility. IT services are provided over a cloud-computing infrastructure made up of geographically distributed data centers. Each data center comprises thousands of server computers, switches, routers, and mass data-storage devices interconnected by local-area networks, wide-area networks, and wireless communications.
Because of the tremendous size of a typical data center, cloud-computing providers rely on automated IT financial management tools to determine cost of IT services, project future costs of IT services, and determine the financial health of a data center. A typical automated management tool determines current and projected cost of IT services based on a reference database of actual data center equipment inventory and corresponding invoice data. But typical management tools do not have access to the latest invoice data for data center equipment. Management tools may deploy web automated computer programs, called web crawling agents, that automatically collect information from a variety of vendor web sites and write the information to the reference database. However, agents are not able to identity errors in web pages and may not be up-to-date with the latest format changes to web sites. As a result, agents often write incorrect information regarding data center equipment to reference databases. Management tools may also compute approximate costs of unrecorded equipment based on equipment currently recorded in a reference database. For example, the cost of an unrecorded server computer may be approximated by computing a mean cost of server computers recorded in the reference database with components that closely match the components of the unrecorded server computer and assigning the mean cost as the approximate cost of the unrecorded server computer. However, this technique for determining the cost of data center equipment typically is unreliable with errors ranging from as low as 12% to as high as 45%. Cloud-computing providers and data center managers seek more accurate tools to determine cost of IT equipment in order to more accurately determine the cost of IT services and project future cost of IT services.